Neoglycolipid probes prepared via oxime ligation for microarray analysis of oligosaccharide-protein interactions

Neoglycolipid technology is the basis of a microarray platform for assigning oligosaccharide ligands for carbohydrate-binding proteins. The strategy for generating the neoglycolipid probes by reductive amination results in ring opening of the core monosaccharides. This often limits applicability to short-chain saccharides, although the majority of recognition motifs are satisfactorily presented with neoglycolipids of longer oligosaccharides. Here, we describe neoglycolipids prepared by oxime ligation. We provide evidence from NMR studies that a significant proportion of the oxime-linked core monosaccharide is in the ring-closed form, and this form selectively interacts with a carbohydrate-binding protein. By microarray analyses we demonstrate the effective presentation with oxime-linked neoglycolipids of (1) Lewis(x) trisaccharide to antibodies to Lewisx, (2) sialyllactose analogs to the sialic acid-binding receptors, siglecs, and (3) N-glycans to a plant lectin that requires an intact N-acetylglucosamine core.

Energy and protein interactions and their effect on nitrogen excretion in dairy cows

The principal driver of nitrogen (N) losses from the body including excretion and secretion in milk is N intake. However, other covariates may also play a role in modifying the partitioning of N. This study tests the hypothesis that N partitioning in dairy cows is affected by energy and protein interactions. A database containing 470 dairy cow observations was collated from calorimetry experiments. The data include N and energy parameters of the diet and N utilization by the animal. Univariate and multivariate meta-analyses that considered both within and between study effects were conducted to generate prediction equations based on N intake alone or with an energy component. The univariate models showed that there was a strong positive linear relationships between N intake and N excretion in faeces, urine and milk. The slopes were 0.28 faeces N, 0.38 urine N and 0.20 milk N. Multivariate model analysis did not improve the fit. Metabolizable energy intake had a significant positive effect on the amount of milk N in proportion to faeces and urine N, which is also supported by other studies. Another measure of energy considered as a covariate to N intake was diet quality or metabolizability (the concentration of metabolizable energy relative to gross energy of the diet). Diet quality also had a positive linear relationship with the proportion of milk N relative to N excreted in faeces and urine. Metabolizability had the largest effect on faeces N due to lower protein digestibility of low quality diets. Urine N was also affected by diet quality and the magnitude of the effect was higher than for milk N. This research shows that including a measure of diet quality as a covariate with N intake in a model of N execration can enhance our understanding of the effects of diet composition on N losses from dairy cows. The new prediction equations developed in this study could be used to monitor N losses from dairy systems.

Protein interactions within the SET1 complex and their roles in the regulation of histone 3 lysine 4 methylation

Set1 is the catalytic subunit and the central component of the evolutionarily conserved Set1 complex (Set1C) that methylates histone 3 lysine 4 (H3K4). Here we have determined protein/protein interactions within the complex and related the substructure to function. The loss of individual Set1C subunits differentially affects Set1 stability, complex integrity, global H3K4 methylation, and distribution of H3K4 methylation along active genes. The complex requires Set1, Swd1, and Swd3 for integrity, and Set1 amount is greatly reduced in the absence of the Swd1-Swd3 heterodimer. Bre2 and Sdc1 also form a heteromeric subunit, which requires the SET domain for interaction with the complex, and Sdc1 strongly interacts with itself. Inactivation of either Bre2 or Sdc1 has very similar effects. Neither is required for complex integrity, and their removal results in an increase of H3K4 mono- and dimethylation and a severe decrease of trimethylation at the 5′ end of active coding regions but a decrease of H3K4 dimethylation at the 3′ end of coding regions. Cells lacking Spp1 have a reduced amount of Set1 and retain a fraction of trimethylated H3K4, whereas cells lacking Shg1 show slightly elevated levels of both di- and trimethylation. Set1C associates with both serine 5- and serine 2-phosphorylated forms of polymerase II, indicating that the association persists to the 3′ end of transcribed genes. Taken together, our results suggest that Set1C subunits stimulate Set1 catalytic activity all along active genes.

Colloid probe AFM study of thermal collapse and protein interactions of poly(N-isopropylacrylamide) coatings

Graft coatings of poly(N-isopropylacrylamide) (pNIPAM) are of considerable interest for the reversible control of bio-interfacial interactions. In this study, graft coatings were prepared by free radical polymerisation from surface-bound polymerisable groups, on silicon wafers and quartz crystal microbalance (QCM) sensors. QCM with dissipation monitoring showed a gradual, extended phase change as the temperature increased. Colloid probe atomic force microscopy (CP-AFM) revealed a marked change in the compressibility of the coating below and above the lower critical solution temperature (LCST). Force curves showed an approximate 9-fold reduction in thickness between 24 °C and 38 °C, yet the collapsed coating at 38 °C still had a thickness significantly higher than the ellipsometrically determined dry thickness, indicating a residual extent of hydration above the LCST. At all temperatures, interaction force curves showed steric repulsion, though over different distances. There was little hysteresis between approach and retract force curves, which is evidence for almost instantaneous relaxation of the coating upon decompression. CP-AFM using a probe coated with bovine serum albumin (BSA) showed repulsive interactions with little approach/retraction hysteresis below the LCST, indicating lack of adhesion between the pNIPAM coating and the BSA-coated probe. In contrast, above the LCST the force curves on retraction were characteristic of adhesion, while the approach curves were still repulsive, and the adhesion increased in strength as the temperature was increased further beyond the LCST. Thus, QCM-D and CP-AFM data correlated well in showing a gradual nature of the phase transition and a concomitant gradual change in the interaction force with BSA.

Iteratively predict protein functions from protein-protein interactions

Current similarity-based approaches of predicting protein functions from protein-protein interaction (PPI) data usually make use of available information in the PPI network to predict functions of un-annotated proteins, and the prediction is a one-off procedure. However the interactions between proteins are more likely to be mutual rather than static and mono-directed. In other words, the un-annotated proteins, once their functions are predicted, will in turn affect the similarities between proteins. In this paper, we propose an innovative iteration algorithm that incorporates this dynamic feature of protein interaction into the protein function prediction, aiming to achieve higher prediction accuracies and get more reasonable results. With our algorithm, instead of one-off function predictions, functions are assigned to an unannotated protein iteratively until the functional similarities between proteins achieve a stable state. The experimental results show that our iterative method can provide better prediction results than one-off prediction methods with higher prediction accuracies, and is stable for large protein datasets.

CHOLESTEROL MODULATION OF LIPID PROTEIN INTERACTIONS IN LIVER MICROSOMAL MEMBRANE - A SPIN LABEL STUDY

ESR spectra of spin probes were used to monitor lipid-protein interactions in native and cholesterol-enriched microsomal membranes. In both systems composite spectra were obtained, one characteristic of bulk bilayer organization and another due to a motionally restricted population, which was ascribed to lipids in a protein microenvironment. Computer spectral subtractions revealed that cholesterol modulates the order/mobility of both populations in opposite ways, i.e., while the lipid bilayer region gives rise to more anisotropic spectra upon cholesterol enrichment, the spectra of the motionally restricted population become indicative of increased mobility and/or decreased order. These events were evidenced by measurement of both effective order parameters and correlation times. The percentages of the motionally restricted component were invariant in native and cholesterol-enriched microsomes. Variable temperature studies also indicated a lack of variation of the percentages of both spectral components, suggesting that the motionally restricted one was not due to protein aggregation. The results correlate well with the effect of cholesterol enrichment on membrane-bound enzyme kinetics and on the behavior of fluorescent probes [Castuma & Brenner (1986) Biochemistry 25, 4733-4738]. Several hypothesis are put forward to explain the molecular mechanism of the cholesterol-induced spectral changes.

Synergy of DNA-bending nucleoid proteins and macromolecular crowding in condensing DNA

Many prokaryotic nucleoid proteins bend DNA and form extended helical protein-DNA fibers rather than condensed structures. On the other hand, it is known that such proteins (such as bacterial HU) strongly promote DNA condensation by macromolecular crowding. Using theoretical arguments, we show that this synergy is a simple consequence of the larger diameter and lower net charge density of the protein-DNA filaments as compared to naked DNA, and hence, should be quite general. To illustrate this generality, we use light-scattering to show that the 7kDa basic archaeal nucleoid protein Sso7d from Sulfolobus solfataricus (known to sharply bend DNA) likewise does not significantly condense DNA by itself. However, the resulting protein-DNA fibers are again highly susceptible to crowding-induced condensation. Clearly, if DNA-bending nucleoid proteins fail to condense DNA in dilute solution, this does not mean that they do not contribute to DNA condensation in the context of the crowded living cell. © 2007 World Scientific Publishing Company.

Bacillus thuringiensis Cry1Ia10 and Vip3Aa protein interactions and their toxicity in Spodoptera spp. (Lepidoptera)

The polyphagous pests belonging to the genus Spodoptera are considered to be among the most important causes of damage and are widely distributed throughout the Americas'. Due to the extensive use of genetically modified plants containing Bacillus thuringiensis genes that code for insecticidal proteins, resistant insects may arise. To prevent the development of resistance, pyramided plants, which express multiple insecticidal proteins that act through distinct mode of actions, can be used. This study analyzed the mechanisms of action for the proteins Cry1Ia10 and Vip3Aa on neonatal Spodoptera frugiperda, Spodoptera albula, Spodoptera eridania and Spodoptera cosmioides larvae. The interactions of these toxins with receptors on the intestinal epithelial membrane were also analyzed by binding biotinylated toxins to brush border membrane vesicles (BBMVs) from the intestines of these insects. A putative receptor of approximately 65. kDa was found by ligand blotting in all of these species. In vitro competition assays using biotinylated proteins have indicated that Vip3Aa and Cry1Ia10 do not compete for the same receptor for S. frugiperda, S. albula and S. cosmioides and that Vip3Aa was more efficient than Cry1Ia10 when tested individually, by bioassays. A synergistic effect of the toxins in S. frugiperda, S. albula and S. cosmioides was observed when they were combined. However, in S. eridania, Cry1Ia10 and Vip3Aa might compete for the same receptor and through bioassays Cry1Ia10 was more efficient than Vip3Aa and showed an antagonistic effect when the proteins were combined. These results suggest that using these genes to develop pyramided plants may not prove effective in preventing the development of resistance in S. eridiana. © 2012 Elsevier Inc.

The Development of a Universal In Silico Predictor of Protein-Protein Interactions

Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.